A Noise Reduction Method for Photoacoustic Imaging In Vivo Based on EMD and Conditional Mutual Information - Meng Zhou; Haibo Xia; Hongtao Zhong; Jiayao Zhang; Fei Gao (IEEE Photonics Journal, 2019)
Photoacoustic tomography is a technique to reconstruct the image of light energy absorption distribution in tissues based on the detected photoacoustic signals. In recent years, this research field has been greatly developed, and its application range is wide, including anatomy, functionality, and molecular imaging. However, the conversion efficiency of photoacoustic effect from light to sound is quite low, which leads to the low signal-to-noise ratio of photoacoustic signal and the poor quality of reconstructed photoacoustic image. The traditional method to improve the signal-to-noise ratio of photoacoustic signals is data averaging method, but it seriously limits the imaging speed due to multiple acquisition. Without sacrificing signal fidelity and imaging speed, an empirical mode decomposition (EMD) combined with conditional mutual information de-noising algorithm for photoacoustic tomography is proposed in this paper. The simulation results and experimental results of photoacoustic signal de-noising achieve significant improvement of signal-to-noise ratio of photoacoustic signal and the enhancement of contrast of the reconstructed image. The simulation results and experimental results show that EMD combined with mutual information method improves at least 2 dB and 3 dB, respectively, more than traditional wavelet threshold method and band-pass filter. The improvement of contrast-to-noise ratio is more than 2 dB and 3 dB, respectively, more than traditional wavelet threshold method and band-pass filter.